By Nicola Scafetta
Although the sun provides nearly all the energy needed to warm the planet, its contribution to climate change remains widely questioned. Many empirically based studies claim that it has a significant effect on climate, while others (often based on computer global climate simulations) claim that it has a small effect.
The Intergovernmental Panel on Climate Change (IPCC) supports the latter view and estimates that almost 100% of the observed warming of the Earth’s surface from 1850–1900 to 2020 was caused by man-made emissions (AR6 WG1, pages 63, 425, and 962). This is known as the anthropogenic global warming (AGWT) theory.
I addressed this important paradox in a new study published in Geoscience Frontiers. The conundrum appears to arise from two sets of uncertainties: (i) the historical decades and long-term variations in solar activity are unknown; (ii) the sun may affect Earth’s climate through various physical mechanisms many of which are not fully understood and are not incorporated into the global climate models (GCMs).
It is important to notice that the AGWT is based solely on computer global climate model simulations that use total solar irradiance (TSI) records with very low multidecadal and long-term variability. The models also assume that the sun affects the climate system only through radiative forcing, although there is evidence that other solar processes related to solar magnetic activity (solar wind, cosmic rays, interplanetary dust, etc.) also affect the climate.
The total solar irradiance (TSI) records
Decadal and longer-term changes in historical solar activity are unknown because total solar irradiance (TSI) reaching Earth can only be accurately measured by satellites, and these records are only available since 1978. However, these data remain controversial, as different trends emerge depending on the combination and processing of records provided by different experimental teams.
Solar activity changes over longer periods are modeled using a number of solar activity proxies (e.g. sunspot records, faculae records, 14C and 10Be cosmogenic records, etc.). Proxy models are uncertain by definition, and the result is that the scientific literature has provided a variety of TSI reconstructions that greatly differ from one another in both their secular trends and multidecadal variability.
I have combined several TSI proxy models, and have evaluated their effective solar radiative forcing functions to be used for climate studies. Figure 1 compares them with each other and with the volcano and anthropogenic effective modeled forcings. The solar effective forcing functions depicted in Fig. 1B differ in several respects.
The solar forcing function currently used in the CMIP6 GCM simulations (green) has remained nearly constant for about 200 years and, furthermore, it has decreased progressively from 1970 to 2020. Thus, by using this TSI record, the CMIP6 GCMs could only conclude that the sun cannot explain the warming observed since the pre-industrial period (1850–1900), and particularly that observed from 1980 to 2020.
On the contrary, the other three TSI records (red, yellow, and black) reveal a multidecadal oscillation as well as a clear increasing secular trend that is closely correlated with the changes observed in total surface temperature records.
Modeling the total solar activity (TSA) change effect on the climate
The total solar effect on the climate cannot be assessed using only the TSI forcing functions because, for example, alternative solar-related mechanisms are claimed to directly modulate cloud cover. However, because the physics of such mechanisms is poorly understood, they cannot be implemented in current GCMs. However, if their impact is shown to be large, current GCMs will be unsuitable to use to model climate change.
I addressed this issue by assuming that the given TSI records are proxies for total solar activity (TSA). In fact, the TSI records are themselves proxies derived from a number of observables (sunspot numbers, 14C and 10Be cosmogenic concentrations, etc.) that, technically speaking, are not “light”. Then I adopted an empirical methodology to assess the TSA effect by evaluating its optimal climate fingerprint together with those produced by the anthropogenic and volcanic radiative forcing functions adopted by the CMIP6 GCMs. The IPCC assumes that the only solar influence on climate is due directly to the change in power delivered to Earth through radiation and that the climate sensitivity to it is equal to that of volcanic and anthropogenic radiative forcing. On the contrary, I assumed that the TSI delivered on Earth is only proportional to the real total solar forcing (which includes TSI and any other possible mechanisms) that could have a climatic impact. In this way, the climate sensitivity to solar activity changes is allowed to be different (e.g. greater) than the climate sensitivity to radiative forcing alone. This was a reasonable assumption given the fact that many studies have pointed out that the climate appears to be oversensitive to TSI changes alone. For example, Javier Vinós and Andy May have noted that the ocean temperature impact from the bottom of the solar cycle to the top is four times larger than can be explained by the change in TSI, as explained in the quote below from here.
“White et al. (2003) analyzed the global tropical diabatic heat storage budget and found that the anomalous heating of the upper layer of the ocean to the depth of the 22°C isotherm yielded a value of ± 0.9 W/m2, that is nearly an order of magnitude larger than the surface radiative forcing of ± 0.1 W/m2 associated with the solar cycle (solar radiative forcing is the ΔTSI/4 x 0.7). Even more, the quasi-decadal temperature change in the upper ocean is phase-locked to the solar cycle, something that modern climatology cannot explain.”See here.
The model reproduces the results of the CMIP6 GCMs when their original forcing functions are applied under similar physical conditions. In this case, the equilibrium climate sensitivity (ECS) was 1.4°C–2.8°C, which is compatible with the low-ECS CMIP6 GCM group. This means that about two-thirds of the current GCMs (whose ECS varies between 1.8°C and 5.7°C) are overestimating anthropogenic warming, as other recent studies have confirmed. AR6 and AR5 acknowledge that the CMIP5 and CMIP6 models overestimate tropical upper air temperature and ocean surface temperatures (AR6, page 443).
However, if the proposed solar records are used as TSA proxies and the climatic sensitivity to them is allowed to differ from the climatic sensitivity to radiative forcings, a much greater solar impact on climate change is found, along with a significantly reduced radiative effect. In this case, the ECS is found to be 0.9°C–1.8°C, with a mean of around 1.3°C. This means that anthropogenic warming is greatly overestimated.
Fig. 2 compares the HadCRUT5 global surface temperature record to (A) the CMIP6 GCM ensemble mean record and (B) the energy balance model using a proposed TSA model that does not use the GCMs’ low-secular-variability TSI record. The GCM simulation depicted in Fig. 2A monotonically warms up (green line). On the contrary, the model provided in Fig. 2B indicates an oscillating pattern developing around a warming trend that reproduces the climatic record far more precisely.
This result suggests that about 80% of the solar influence on the climate may not be induced by TSI forcing alone, but rather by other sun-climate processes (e.g., by a solar magnetic modulation of cosmic ray and other particle fluxes, and/or others). These alternative mechanisms must be thoroughly investigated and physically understood before trustworthy GCMs can be created to correctly interpret climate change, whether anthropogenic or natural, and produce reliable future climate change projections.
Prof. Dr. Nicola Scafetta works in the Department of Earth Sciences, Environment and Georesources, University of Naples Federico II, Naples, Italy.
This post originally appeared, in slightly different form, on Phys.Org.
IPCC. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, . . . B. Zhou (Ed.)., WG1. Retrieved from https://www.ipcc.ch/report/ar6/wg1/
Scafetta, N. (2023). Empirical assessment of the role of the Sun in climate change using balanced multi-proxy solar records. Geoscience Frontiers, 14(6), 101650. Retrieved from https://doi.org/10.1016/j.gsf.2023.101650